State of AI for Earth Observation (preprint)

Hello. I'd like to share here a potentially valuable resource for those looking to understand how AI is transforming remote sensing, or get into the field of Earth Observation. (See also related Twitter thread: https://twitter.com/alkalait/status/1565710662658953222?s=20...).

Most of the images generated by satellites will never be seen by human eyes. There simply aren't enough humans on Earth to sift through the TBs of imagery acquired daily by satellites. Artificial Intelligence is revolutionising many sectors, including Earth Observation.

[Cover.](https://preview.redd.it/avrdtspt7am91.png?width=1449&format=...)

Our preprint of *State of AI for Earth Observation: a concise overview from sensors to applications* serves as an intro to

* sensors

* the core ideas in deep learning for EO, and the current state of research

* how and where AI is applied in EO

* where AI4EO is headed

* and the role of research and technology organisations.

You can download the preprint here (no sign-up needed): https://sa.catapult.org.uk/digital-library/white-paper-state...

EO, Remote Sensing, ML are all independent fields of study, with several textbooks dedicated to each. Despite this, the conglomeration of ML + Remote Sensing + EO (aka. AI4EO) raises basic questions that are rarely motivated in isolated fields. For example, how can we...

* tell what happens on Earth based on observations from space?

* allow data tell the story of a natural or anthropogenic phenomenon?

* meaningfully combine sensors of fundamentally different mechanics?

* place all data streams on the globe continuously and harmoniously?

* do all of the above, mindful of noise, errors and observation gaps?

* Finally, how do we walk away with knowledge of what we don’t yet know?

To appeal to all backgrounds, we have included a handy glossary and an acronym explainer.

[Glossary.](https://preview.redd.it/6do66r009am91.png?width=718&format=p...)

This work is now under peer-review. In the meantime instead of uploading it on arXiv, Satellite Applications Catapult (an Innovate UK center) is hosting it as a white paper (no sign-up needed). If you find it useful, please spread the word, or retweet this thread: https://twitter.com/alkalait/status/1565710662658953222?s=20...

Enjoy.